Title: Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites
Authors: MITCHARD E. T. A.FELDPAUSCH TedBRIENEN RLOPEZ-GONZALEZ GMONTEAGUDO AbelBAKER TLEWIS SLLOYD JQUESADA Carlos A.GLOOR ManuelTER STEEGE HansMEIR P.ALVAREZ EstebanARAUJO-MURAKAMI AlejandroARAGÃO Luiz E. O. C.ARROYO LuzmilaAYMARD GBANKI OBONAL DamienBROWN SandraBROWN Foster I.CERÓN Carlos E.MOSCOSO Victor ChamaCHAVE JeromeCOMISKEY James A.CORNEJO FernandoMEDINA Massiel CorralesDA COSTA LolaCOSTA Flavia R. C.DI FIORE AnthonyDOMINGUES Tomas F.ERWIN TerryFREDERICKSON ToddHIGUCHI NiroCORONADO Euridice N. HonorioKILLEEN Tim J.LAURANCE William FLEVIS CarolinaMAGNUSSON William E.MARIMON Beatriz S.JUNIOR Ben Hur MarimonPOLO Irina MendozaMISHRA PiyushNASCIMENTO Marcelo T.NEILL DavidVARGAS Mario P. NúñezPALACIOS Walter A.PARADA AlexanderMOLINA Guido PardoPEÑA-CLAROS MarielosPITMAN NigelPERES Carlos A.POORTER LourensPRIETO AdrianaRAMIREZ-ANGULO HirmaCORREA Zorayda RestrepoROOPSIND AnandROUCOUX Katherine H.RUDAS AgustinSALOMÃO Rafael P.SCHIETTI JulianaSILVEIRA MarcosDE SOUZA Priscila F.STEININGER Mark K.STROPP CARNEIRO JULIANATERBORGH JohnTHOMAS RaquelTOLEDO MarisolTORRES-LEZAMA ArmandoVAN ANDEL Tinde R.VAN DER HEIJDEN GeertjeVIEIRA Ima C. G.VIEIRA SimoneVILANOVA-TORRE EmilioVOS Vincent A.WANG OpheliaZARTMAN Charles E.MALHI YadvinderPHILLIPS Oliver L.
Citation: GLOBAL ECOLOGY AND BIOGEOGRAPHY vol. 23 no. 8 p. 935-946
Publisher: WILEY-BLACKWELL
Publication Year: 2014
JRC N°: JRC94032
ISSN: 1466-822X
URI: http://onlinelibrary.wiley.com/doi/10.1111/geb.12168/abstract;jsessionid=36767025612453FC6E376E1120DEF151.f04t01
http://publications.jrc.ec.europa.eu/repository/handle/JRC94032
DOI: 10.1111/geb.12168
Type: Articles in periodicals and books
Abstract: ABSTRACT Aim The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/ 2014_1 Methods Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Main conclusions Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.
JRC Directorate:Sustainable Resources

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